Daniel Kifer

Professor of Computer Science & Engineering

Daniel Kifer

Publication Tags

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Learning Convolutional Neural Networks Travel Time Semantics Soil Moisture Neurons Big Data Moisture Trajectories Pixels Deep Learning Opinion Neural Networks Coding Crime Deep Neural Networks Science Baseline Prolongation Image Compression Landslide Hydrology Brain Trajectory Availability

Most Recent Publications

Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes

Prabhav Borate, Jacques Rivière, Chris Marone, Ankur Mali, Daniel Kifer, Parisa Shokouhi, 2023, Nature Communications

Differentiable modelling to unify machine learning and physical models for geosciences

Chaopeng Shen, Alison P. Appling, Pierre Gentine, Toshiyuki Bandai, Hoshin Gupta, Alexandre Tartakovsky, Marco Baity-Jesi, Fabrizio Fenicia, Daniel Kifer, Li Li, Xiaofeng Liu, Wei Ren, Yi Zheng, Ciaran J. Harman, Martyn Clark, Matthew Farthing, Dapeng Feng, Praveen Kumar, Doaa Aboelyazeed, Farshid Rahmani, Yalan Song, Hylke E. Beck, Tadd Bindas, Dipankar Dwivedi, Kuai Fang, Marvin Höge, Chris Rackauckas, Binayak Mohanty, Tirthankar Roy, Chonggang Xu, Kathryn Lawson, 2023, Nature Reviews Earth and Environment on p. 552-567

Backpropagation-Free Deep Learning with Recursive Local Representation Alignment

Alexander G. Ororbia, Ankur Mali, Daniel Kifer, C. Lee Giles, 2023, on p. 9327-9335

Answering Private Linear Queries Adaptively using the Common Mechanism

Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer, 2023, Proceedings of the VLDB Endowment on p. 1883-1896

The neural coding framework for learning generative models

Alexander Ororbia, Daniel Kifer, 2022, Nature Communications

Free gap estimates from the exponential mechanism, sparse vector, noisy max and related algorithms

Zeyu Ding, Yuxin Wang, Wang Yuxin, Yingtai Xiao, Guanhong Wang, Danfeng Zhang, D Kifer, Daniel Kifer, 2022, VLDB Journal on p. 23-48

The 2020 census disclosure avoidance system TopDown algorithm.

John Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson Garfinkel, Micah Heineck, Christine Heiss, Robert Johns, Daniel Kifer, Philip Leclerc, Ashwin Machanavajjhala, Brett Moran, William Sexton, Matthew Spence, Pavel Zhuravlev, 2022, Harvard Data Science Review

Lifelong Neural Predictive Coding: Learning Cumulatively Online without Forgetting

Alexander G. Ororbia, C. Lee Giles, Ankur Mali, Daniel Kifer, 2022,

Constructing a Large-Scale Landslide Database Across Heterogeneous Environments Using Task-Specific Model Updates

S. Nagendra, Daniel Kifer, S. Manjunatha, Benjamin Mirus, Kathryn Lawson, D Kifer, T. Pei, Daniel Kifer, W. Li, Kathryn Lawson, Te Pei, Srikanth Banagere Manjunatha, Benjamin Mirus, K. Lawson, H. Nguyen, Weixin Li Li, Hien Nguyen, Tong Qiu, S. Tran, T Qiu, Chaopeng Shen, C Shen, Sarah Tran, Chaopeng Shen, 2022, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing on p. 4349-4370

Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder

Ankur Mali, Alexander Ororbia, II, Alexander Ororbia, Daniel Kifer, Clyde Giles, 2022, CoRR on p. 471

Most-Cited Papers

Pufferfish: A framework for mathematical privacy definitions

Daniel Kifer, Ashwin Machanavajjhala, 2014, ACM Transactions on Database Systems

Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network

Kuai Fang, Chaopeng Shen, Daniel Kifer, Xiao Yang, 2017, Geophysical Research Letters on p. 11,030-11,039

HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community

Chaopeng Shen, Eric Laloy, Amin Elshorbagy, Adrian Albert, Jerad Bales, Fi John Chang, Sangram Ganguly, Kuo Lin Hsu, Daniel Kifer, Zheng Fang, Kuai Fang, Dongfeng Li, Xiaodong Li, Wen Ping Tsai, 2018, Hydrology and Earth System Sciences on p. 5639-5656

Learning to extract semantic structure from documents using multimodal fully convolutional neural networks

Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, Clyde Giles, 2017, on p. 4342–4351

Crime rate inference with big data

Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li, 2016, on p. 635-644

Learning to read irregular text with attention mechanisms

Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles, 2017, on p. 3280-3286

A Simple Baseline for Travel Time Estimation using Large-scale Trip Data

Hongjian Wang, Xianfeng Tang, Yu Hsuan Kuo, Daniel Kifer, Zhenhui Li, 2019, ACM Transactions on Intelligent Systems and Technology

Multi-Scale Multi-Task FCN for Semantic Page Segmentation and Table Detection

Dafang He, Scott Cohen, Brian Price, Daniel Kifer, C. Lee Giles, 2017, on p. 254-261

Concentrated differentially private gradient descent with adaptive per-iteration privacy budget

Jaewoo Lee, Daniel Kifer, 2018, on p. 1656-1665

A neural temporal model for human motion prediction

Anand Gopalakrishnan, Ankur Mali, Dan Kifer, Lee Giles, Alexander G. Ororbia, 2019, on p. 12108-12117